The worldwide increase in obesity has been accompanied by an increase in diabetes, hypertension, dyslipidemia, and non-alcoholic fatty liver disease (NAFLD). NAFLD can result in liver cirrhosis and eventual liver failure. If detected early, accumulation of fat in the liver can be reduced with weight loss or medications. The burden of disease from, best correlates of, and metabolic significance of fatty liver in large population-based samples however, remain largely unknown. Fortunately, over 3500 individuals from the Framingham Heart Study cohort, a community and family-based cohort of over 14,000 individuals, have had abdominal computed tomograms (CTs) which can be quantified for fatty liver. In the Framingham Heart Study Cohort we propose to: Aim 1. Determine the prevalence of fatty liver. We will read the over 3500 CT scans available in this study sample for the presence of fatty liver and determine the overall and age and sex-specific prevalence of this condition. Aim 2. Determine the clinical correlates of fatty liver. Using multivariate logistic regression modeling in a cross sectionally designed study, we will test whether measures of adiposity including body mass index (BMI), waist circumference (WC), subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) as well as metabolic risk factors including impaired fasting glucose (IFG), diabetes (DM), hypertension (HTN) and dyslipidemia independently correlate with fatty liver. Furthermore, we will test whether the presence of coronary artery calcium correlates with fatty liver. Aim 3. Determine the heritability of fatty liver. We will take advantage of the family-based component of the cohort to estimate the heritability of fatty liver using variance-components likelihood methods. Aim 4. Test whether genetic variants that are associated with obesity and diabetes are also associated with fatty liver. We will test whether obesity or diabetes-associated single nucleotide polymorphisms (SNPs) in genes INSIG2, KCNJ11, PPARG, and 7CF7L2 also associate with fatty liver. The work proposed in this application aims to characterize fatty liver in a large population based cohort to learn more about the clinical, biochemical and genetic correlates and risk factors of fatty liver. With a better understanding of fatty liver disease risk factors we may be able to identify and treat people with fatty liver earlier in the course of their disease and thus improve their outcome. Furthermore, we will learn whether the presence of fatty liver correlates with the presence of preclinical cardiovascular disease compared to visceral to subcutaneous deposition of fat which may help risk stratify such individuals for intervention. [unreadable] [unreadable] [unreadable] [unreadable]